Abstract
Chronic hepatitis C is a disease that is difficult to treat. At present, interferon might be the only drug, which can cure this kind of disease, but its efficacy is limited and patients face the risk of side effects and high expense, so doctors considering interferon must make a serious choice. The purpose of this study is to establish a simple model and use the clinical data to predict the interferon efficacy. This model is a combination of Feature Subset Selection and the Classifier using a Support Vector Machine (SVM). The study indicates that when five features have been selected, the identification by the SVM is as follows: the identification rate for the effective group is 85%, and the ineffective group 83%. Analysis of selected features show that HCV-RNA level, hepatobiopsy, HCV genotype, ALP and CHE are the most significant features. The results thus serve for the doctors’ reference when they make decisions regarding interferon treatment.
Similar content being viewed by others
References
Hoofnagle, J. H., Mullen, K. D., Jones, D. B., and Rustgi, V., Treatment of chronic non-A, non-B hepatitis with recombinant human alpha interferon. A preliminary report. N. Engl. J. Med. 315:1575–1578, 1986.
Davis, G. L., Balart, L. A., Schiff, E. R., and Lindsay, K., Treatment of chronic hepatitis C with recombinant interferon alfa. A multicenter randomized, controlled trial. N. Engl. J. Med. 321:1501–1506, 1989.
Di Bisceglie, A. M., Martin, P., Kassianides, C., and Lisker-Melman, M., Recombinant interferon alfa therapy for chronic hepatitis C. A randomized, double-blind, placebo-controlled trial. N. Engl. J. Med. 321:1506–1510, 1989.
Hagiwara, H., Hayashi, N., Mita, E., and Ueda, K., Detection of hepatitis C virus RNA in serum of patients with chronic hepatitis C treated with interferon—alpha. Hepatology. 15:37–41, 1992.
Lai, M. Y., Kao, J. H., Yang, P. M., Wang, J. T., Chen, P. J., Chan, K. W, Chu, J. S., and Chen, D. S., Long-term efficacy of ribavirin plus interferon alfa in the treatment of chronic hepatitis C. Gastroenterology. 111:1307–1312, 1996.
Reichard, O., Norkrans, G., Fryden, A., Braconier, J. H., Sonnerborg, A., and Weiland O. Randomised, double-blind, placebo-controlled trial of interferon α-2b with and without ribavirin for chronic hepatitis C. Lancet. 351:83–87, 1998.
Manns, M. P., McHutchison, J. G., Gordon, S. C., Rustgi, V. K., Shiffman, M, Reindollar, R., Goodman, Z. D., Koury, K., Ling, M. H., and Albrecht, J. K. Peginterferon alfa-2b plus ribavirin compared with interferon alfa-2b plus ribavirin for initial treatment of chronic hepatitis C: a randomised trial. Lancet. 358:958–965, 2001.
Fried, M. W., Schiffman, M. L., Reddy, K. R., Smith, C., Marinos, G., Goncales, F. L., Hãussinger, D., Diago, M., Carosi, G., Dhumeaux, D., Craxi, A., Lin, A., Hoffman, J., and Yu, J. Peginterferon alfa-2a plus ribavirin for chronic hepatitis C virus infection. N. Engl. J. Med. 347:975–982, 2002.
Duda, R. O., Hart, P. E & Stork, D. G. Pattern Classification (2nd ed.). Wiley Interscience. New York, NY, 2000.
Cristianini, N., and Shawe-Taylor, J. An Introduction to Support Vector Machines (and other kernel-based learning methods). Cambridge University Press. 2000.
EASL Intemational Consensus Conference on hepatitis C. Paris, 26-28, February 1999 Consensus statement. Journal of Hepatology. 30(5): 956–961, 1999.
Kiyosawa, K., Sodeyama, T., Tanaka, E., and Gibo, Y. Interrelationship of blood transfusion, non-A, non-B hepatitis and hepatocellular carcinoma: analysis by detection of antibody to hepatitis C virus. Hepatology. 12:671–675, 1990.
Tong, M. J., el-Farra, N. S., Reikes, A. R., and Co, R. L. Clinical outcomes after transfusion-associated hepatitis C. N. Engl. J. Med. 332:1463–1466, 1995.
Kanai, K., Kako, M., Aikawa, T., and Kumada, T. Clearance of serum hepatitis C virus RNA after interferon therapy in relation to virus genotype. Liver. 15:185–188, 1995.
Kiyosawa, K. The value of hepatitis C virus genotyping to epidemiological and clinical studies. J. Gastroenterol. Hepatol. 12:623–624, 1997.
Chayama, K., Tsubota, A., Kobayashi, M., and Okamoto, K. Pretreatment virus load and multiple amino acid substitutions in the interferon sensitivity-determining region predict the outcome of interferon treatment in patients with chronic genotype 1b hepatitis C virus infection. Hepatology. 25:745–749, 1997.
Kanai, K., Kako, M., and Okamoto, H., HCV genotypes in chronic hepatitis C and response to interferon. Lancet. 339:1543, 1992.
Yoshioka, K., Kakumu, S., Wakita, T., and Ishikawa, T. Detection of hepatitis C virus by polymerase chain reaction and response to interferon-α therapy: relationship to genotypes of hepatitis C virus. Hepatology. 16:293–299, 1992.
Nousbaum, J. B., Pol, S., Naloas, B., and Landais, P. Hepatitis C virus type 1b(II) infection in France and Italy. Ann. Intern. Med. 122:161–168, 1995.
Davis, G. L., and Lau, J. Y. Factors predictive of a beneficial response to therapy of hepatitis C. Hepatology. 26(suppl):122S–127S, 1997.
Kuo, G., Choo, Q. L., Alter, H. J., and Gitnick, G. L., An assay for circulating antibodies to a major etiologic virus of human non-A, non-B hepatitis. Science. 244:362–364, 1989
Shiratori, S., Kato, N., Yokosuka, O., and Imazeki, F., Predictors of the efficacy of interferon therapy in chronic hepatitis C virus infection. Tokyo-Chiba Hepatitis Research Group. Gastroenterology. 113:558–566, 1997.
Poynard, T., Bedossa, P., Chevallier, M., and Mathurin, P., A comparison of three interferon alfa-2b regimens for the long-term treatment of chronic non-A, non-B hepatitis. N. Engl. J. Med. 332:1457–1462, 1995.
Lau, J. Y., Davis, G. L., Kniffen, J., and Qian, K. P., Significance of serum hepatitis C virus RNA levels in chronic hepatitis C. Lancet. 341:1501–1504, 1993.
Bishop, C., M., Neural Networks for Pattern Recognition, Oxford University Press, 1995.
Takahashi, M., Saito, H., Higashimoto, M., Atsukawa, K., and Ishii, H. Benefit of hepatitis C virus core antigen assay in prediction of therapeutic response to interferon and ribavirin combination therapy. J. Clin Microbiol. 43(1):186–191, 2005.
Hwang, Y., Chen, E. Y., Gu, Z. J., Chuang, W. L., Yu, M. L., Lai, M. Y., Chao, Y. C., Lee, C. M., Wang, J. H., Dai, C. Y., Shian-Jy Bey, M., Liao, Y. T., Chen, P. J., and Chen, D. S. Genetic predisposition of responsiveness to therapy for chronic hepatitis C. Pharmacogenomics. 7(5):697–709, 2006.
Kim, S, R., Hayashi, Y., Yoon, S., Taniguchi, M., Yang, M. K., Kim, K. I., Kim, M. M., Saeki, K., Nukata, I., and Imoto, S. Prediction of efficacy of interferon treatment of chronic hepatitis C by multivariate analysis and a new classification. Pathol Int. 48(3):215–220, 1998.
Acknowledgements
J.Y and A.S.N contributed equally to this study. The research of A.S.N is partially supported by a Grant-in-Aid for Private University High-Tech Research Center from the Ministry of Education, Culture, Sports, Science and Technology of Japan.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Yang, J., Nugroho, A.S., Yamauchi, K. et al. Efficacy of Interferon Treatment for Chronic Hepatitis C Predicted by Feature Subset Selection and Support Vector Machine. J Med Syst 31, 117–123 (2007). https://doi.org/10.1007/s10916-006-9046-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10916-006-9046-8